Singapore Institute of Technology

Indriyati Atmosukarto

Associate Professor (Information and computing sciences)


Indriyati Atmosukarto is an Associate Professor at the Singapore Institute of Technology. She is currently the Deputy Cluster Director of the InfoComm Technology (ICT) Cluster. Prior to joining SIT, she was a Research Scientist at the Advanced Digital Sciences Center (ADSC), a joint research center between UIUC and A*STAR in Singapore. At ADSC, Indri was the team lead of the "Semantic Analysis of Video" project. Prior to joining ADSC, Indri was a Postdoctoral Senior Fellow in the Department of Pediatrics, School of Medicine at the University of Washington in Seattle, working at the Seattle Children's Research Institute. She earned her PhD (2010) and MSc (2006) in the Department of Computer Science and Engineering at the University of Washington ,Seattle. She obtained her MSc (2002)and BSc (2000) from the National University of Singapore. Her research interests are in computer vision ( image and video analytics), machine learning, and medical imaging.


  • Acquiring 3D models from images for multimedia systems
  • Craniofacial image analysis
  • 3D object retrieval using salient views
  • A topic model approach to represent and classify american football plays
  • Action recognition using discriminative structured trajectory groups
  • Video analytics in train cabin using deep learning
  • Image Analytics for Train Crowd Estimation
  • Mixture of heterogeneous attribute analyzers for human action detection
  • Recognizing team formation in american football
  • Video Analytics for Indoor Crowd Estimation
  • Trajectory-based Fisher kernel representation for action recognition in videos
  • 3D object classification using salient point patterns with application to craniofacial research
  • 3d object retrieval using salient views
  • Automatic recognition of offensive team formation in american football plays
  • GPLAB: Software review
  • The use of genetic programming for learning 3D craniofacial shape quantifications
  • Skull retrieval for craniosynostosis using sparse logistic regression models
  • A model of multimodal fusion for medical applications
  • Longitudinal, three-dimensional analysis of head shape in children with and without deformational plagiocephaly or brachycephaly
  • Three-dimensional head shape quantification for infants with and without deformational plagiocephaly
  • 3D model retrieval with morphing-based geometric and topological feature maps
  • A salient-point signature for 3D object retrieval
  • Shape-based classification of 3D head data
  • An interactive 3D user interface for guided bronchoscopy
  • Automatic 3D shape severity quantification and localization for deformational plagiocephaly
  • A learning approach to 3D object representation for classification
  • Feature combination and relevance feedback for 3D model retrieval
  • Similarity-based retrieval for biomedical applications
  • Object and event recognition for aerial surveillance
  • A similarity retrieval method for functional magnetic resonance imaging (fMRI) statistical maps
  • Polygonizing non-uniformly distributed 3D points by advancing mesh frontiers
  • Mesh construction from non-uniformly distributed and noisy 3D points recovered from image sequence
  • Predator-Miner: Ad hoc mining of associations rules within a database management system
  • The Impact of Tweets, Mandates, Hesitancy and Partisanship on Vaccination Rates
  • TransLine: transfer learning for accurate and explainable power line anomaly detection with insufficient data
  • The implementation of chatbot-mediated immediacy for synchronous communication in an online chemistry course
  • Improving Operational Processes for COVID-19 Ready Smart Campus
  • SynthDa: Exploiting Existing Real-World Data for Usable and Accessible Synthetic Data Generation

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Co-workers & collaborators

Chek Tien Tan

Chek Tien Tan

Cheng Lock, Donny Soh

Cheng Lock, Donny Soh

Indriyati Atmosukarto's public data